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This week’s guest is Rafael Broshi, co-founder & CEO of Notch — the company pioneering resolution-first AI agents. Notch isn’t about smarter chatbots or reply-only wrappers. It’s about agents that solve customer problems end-to-end: issuing refunds, verifying accounts, processing claims, and more.
The results? 40x faster response times, 80% lower cost to serve, and double-digit lifts in conversion rates. Enterprises like Mixtiles and Guardio are already replacing bloated tier-one teams with lean, AI-first operations powered by Notch.
Before founding Notch, Rafael spent a decade in the Air Force, led product strategy at AGT International, and invested with Foundation Partners. His career across defense, product, and investing shaped how he builds AI for mission-critical production environments — not just slick demos.
“Reply-only AI caps at 70% accuracy.
Resolution-first means orchestrating agents and deterministic rules until you’re at 95–99% — good enough for production, not just POCs.”
This one’s for founders designing AI-native orgs, operators buried under CX costs, and execs rethinking how support turns from a cost center into a growth engine.
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In This Episode
Why reply-only bots are a dead end — and what resolution-first unlocks
How autonomous agents are already closing millions of tickets end-to-end
The GTM playbook for replacing bloated support orgs with lean AI-first operations
Why agentic architecture = rules + workflows + LLMs (not just “throw it to a model”)
How Notch drives both cost savings and revenue growth
Which industries are adopting fastest (finance & telecom may surprise you)
Why CX orgs in 2027 could be 70% smaller — and more strategic than ever
5 GTM Takeaways to Steal
Reply-Only Is Dead – Bots that just answer FAQs cap at 70–80% accuracy. Production requires 95–99%.
Orchestration Beats One Model – Agentic workflows + deterministic rules scale where single LLMs fail.
Cost Is the Wedge, Growth Is the Hook – Notch clients triple VIP campaign response rates with AI sales assistants.
Managed Service = GTM Channel – Every successful implementation drives 3–5 warm referrals.
Process Discipline Is Underrated – Clear SOPs make AI adoption 10x faster and easier to scale.
Episode Highlights
00:00 – Intro: Meet Rafael Broshi (Notch)
02:36 – Why CX was broken and ripe for reinvention
03:10 – From chatbots to resolution-first AI
04:28 – Why LLMs cap at 70–80% accuracy in production
06:57 – Inside agentic architecture: rules and LLM workflows
10:09 – Replicating tone, policies, and company voice
12:04 – Case study: 3x revenue lift with AI sales assistant Ella
14:29 – Metrics that matter: CSAT, cost-to-serve, conversion
15:48 – Early ICPs: e-commerce, finance, telecom
16:59 – Why managed service beats ads as GTM motion
18:26 – Balancing product and service in enterprise AI
19:50 – When autonomous agents go mainstream
20:45 – Overrated vs underrated AI trends in CX
22:00 – What a CX org looks like in 2027
24:31 – When founders should start designing AI-first orgs
25:59 – Lessons from Air Force and VC shaping GTM
26:49 – Selling AI in production vs demo environments
28:01 – Rapid Fire
Further Reading
Want to go deeper? Related GTM Vault playbooks & frameworks:
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Connect
Follow Rafael Broshi: LinkedIn // Notch
Follow Rick Koleta: LinkedIn // RiteGTM
Resolution-first AI isn’t just fixing support. It’s redefining what lean, AI-native GTM looks like.
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